Lipoprotein(a) is associated with premature coronary artery disease: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Lipoprotein(a) is associated with adverse cardiovascular outcomes and its association with premature coronary artery disease (pCAD) is underexamined. The primary aim of the study is to compare serum lipoprotein(a) levels between pCAD cases and controls. METHODS: We conducted a systematic review and the MEDLINE database, ClinicalTrials.gov, medRxiv and Cochrane Library were searched for studies evaluating lipoprotein(a) and pCAD. Standardized mean differences (SMD) of lipoprotein(a) in pCAD patients versus the controls were pooled by a random-effects meta-analysis. The presence of statistical heterogeneity was evaluated with the Cochran Q chi-square test and the quality of the included studies was assessed via the Newcastle-Ottawa Scale. RESULTS: A total of 11 studies were found eligible, reporting on the difference in lipoprotein(a) levels between pCAD patients and controls. Serum lipoprotein(a) concentration was found significantly increased in patients with pCAD (SMD = 0.97; 95% confidence intervals, 0.52-1.42; P < 0.0001; I2 = 98%) as compared to controls. High statistical heterogeneity and relatively small case-control studies of moderate quality are the main limitations of this meta-analysis. CONCLUSION: Lipoprotein(a) levels are significantly increased in patients with pCAD as compared to controls. Further studies are needed to clarify the clinical significance of this finding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.042 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".